The data engineer is one of the highest paying data roles with relatively low competition and a great future. But what does the data engineer actually do? The simple answer is that they designed, build and maintain the infrastructure for collecting, storing and analyzing data, ensuring it's accessible, reliable and optimized for performance. But this is a very broad explanation. So let's get into the details of what indeed engineer would do day to day, the responsibilities you may have, the exact skills you need, how much data engineers make and finally, I'll compare the data engineer to other data roles, because that is going to give you a complete understanding of this role. When you understand how a data engineer interacts with other data roles in a team. Let's get started. The engineer might start today by monitoring and checking the health and operating of different data pipelines and databases, because it's going to be up to them to ensure that things run smoothly. The data fuels other business functions, such as the work of a data analyst or a data scientist. So it's important that everything works. Next, they may optimize the performance of the databases and data processing tasks because dealing with large data sets take a lot of time and power. So we want to make things efficient. Now, when it comes to more specific tasks, the engineer is responsible for developing and maintaining ETL processes. ETL stands for Extract Transform Load, and it's basically about getting the right data from various sources into the right places where we need it. For example, our own database. Next, a data engineer might do some data cleansing because through all of this we need to make sure that the data we have is of high quality and that it doesn't contain any problems. Of course, you also want the data in the right format during the day or during the week. A data engineer will also collaborate multiple times with other team members and stakeholders like data scientists, analysts and other clients. For example, it can be requesting access to the right data or just making sure we're meeting all the expectations. Of course, a data engineer will do more things. They may create documentation, security measures and explore ways to upgrade the existing systems for increased efficiency and better capabilities. But these are some of the core responsibilities of a data engineer. Today, let's talk about the salary you can expect as a data engineer, and then we'll talk more about the in-depth skills and compared the data engineer to the other data roles in the US. When you start off as a data engineer, you're going to make roughly 100,000. It's going to depend a lot on your state, the company and so on. But we can see that according to Glassdoor, the range is about 83 to 130000. For a data engineer. For a senior data engineer, the average salary is around 136,000 per year, of course, with a large range, depending on different factors. And for you lead engineer, we're looking at around an average of 153,000 per year. Even if you're not located in the US, I think it should still give you a general understanding of the salary level and the data engineer. It paid it very well. Now let's quickly cover the skills to become a data engineer. This is according to indeed popular employment websites. First we have the coding skills. He did engineer will have solid programing skills with Python being really important for data engineers. They can also use a variety of other programing languages depending on the situation to accomplish tasks. So you do need to have strong programing fundamentals. Next, you'll want to be familiar with database systems and database management. To do this, you will need to know sequel, which is a key skill, knowledge of diverse database solutions and an understanding of data. Warehousing is also essential. Now to work with big data. As a data engineer, you will need to understand the relevant tools. For example, Apache Spark Cloud is also very important in today's landscape as a data engineer, where Microsoft Azure, a US and Google Cloud platform and so on are really important skills and these are the most popular as well. Now I do want to emphasize that you don't need to learn them all, but rather look at what companies you want to work at and what they use. If you don't know this, that's completely fine. And I think that's normal. US and Microsoft, these are some of the most popular. It is also necessary to have a strong understanding of data analysis in itself. But in general, landing a data engineering role is not going to be the easiest thing because your work is really critical and can cause a lot of damage. It's done incorrectly. So you could run the data pipeline or whatever, and therefore you often need some data experience before you become a data engineer. I could mention a lot of more things, but I feel like there's no need in repeating myself. The data engineer is going to do a lot of different things. I could talk for days, but these are really the key skills. It's still unclear. Here is a job listing from a major tech company where you can see what they actually desire yourself. Now we're going to compare it to some other data roles. And when comparing the data engineer to other data roles, it is clear that your focus more on the architecture itself of the data and you're kind of building the foundation for the data in the company. This data may then be used by other team members for analysis, for machine learning or whatever. You're not really going to work in the spotlight, but your work is really important. Now, the data engineer is just one of many amazing data rules. And to learn more about other data rules as well, check out this video next. And have an amazing week, guys.